Background and Purpose: Agent-based modelling and simulation (ABS) is growing in many areas like, e.g., management, social and computer sciences. However, the similar trend does not seem to occur within the field of business process management (BPM), even though simulation approaches like discrete event simulation or system dynamics are well established and widely used. Thus, in our paper we investigate the advantages and disadvantages of agent-based modelling and simulation in the field of BPM in simulation experiments.
Design/Methodology/Approach: In our research, we investigate if there is a necessity for ABS in the field of BPM with our own simulation experiments to compare traditional and ABS models. For this purpose, we use simulation framework MAREA, which is a simulation environment with integrated ERP system. Our model is a complex system of a trading company selling computer cables. For the verification of our model, we use automated process discovery techniques.
Results: In our simulations, we investigated the impact of changes in resources’ behavior on the outcome of company’s order to cash process (O2C). Simulations experiments demonstrated that even small changes might have statistically significant effect on outcomes of the processes and decisions based on such outcomes. Simulation experiments also demonstrated that the impact of randomly distributed fluctuations of well-being have a diminishing tendency with the increasing number of sales representatives involved in the process.
Conclusions: Our research revealed several advantages and disadvantages of using ABS in business process modelling. However, as we show, many of them were at least partially addressed in the recent years. Thus, we believe that ABS will get more attention in the field of BPM similarly to other fields like, e.g., social sciences. We suggested areas in BPM simulations, e.g., modelling of resources, be it human or technological resources, where there is a need for ABS.
Background and Purpose: Motivation of this research is to explore the current trend in automating the business processes through software robots (Robotic Process Automation – RPA) and its managing within enterprise environment where most of the processes are executed by human workforce. As the RPA technology expands the demand for its coordinating grows as well. The possible solution to this challenge is shown in case study research in form of implementing orchestration platform to a concrete business process of onboarding in HR department of a multinational company. The aim of this paper is to explore the phases and activities of the pilot project implementation of Robotic Service Orchestration (RSO) in combination with RPA technology and to assess the potential benefits.
Design/Methodology/Approach: Case study research approach was selected to explore the research phenomena, which is the implementation of RSO platform in combination with RPA technology and assessing incoming benefits. The case is formed with 2 companies – (1) multinational company with ongoing effort of automating onboarding process, (2) technology and consulting company delivering the automation solution. Data were collected through semi-structured interviews with respondents from two involved companies and by analysing internal documents.
Results: The analysis of case provided in this paper revealed some key insights: (1) strategical position of RSO and tactical position of RPA towards the existing legacy systems, (2) need for increased focus on initial process modelling phase, (3) Application Programming Interface (API) integration is more viable solution for RPA, (4) the biggest benefit of RPA - its agility, (5) future potential of the RSO replacing the BPMS.
Conclusions: First of all, there is a need of higher number of software robots adopted in a company before orchestration could pay off. On the other side, current Business Process Management Systems (BPMS) solutions don’t offer functionalities for managing human and software robots workforce altogether. RPA is expected to expand and without proper orchestration the effectivity will not grow constantly.
The simulation and modelling paradigms have significantly shifted in recent years under the influence of the Industry 4.0 concept. There is a requirement for a much higher level of detail and a lower level of abstraction within the simulation of a modelled system that continuously develops. Consequently, higher demands are placed on the construction of automated process models. Such a possibility is provided by automated process discovery techniques. Thus, the paper aims to investigate the performance of automated process discovery techniques within the controlled environment. The presented paper aims to benchmark the automated discovery techniques regarding realistic simulation models within the controlled environment and, more specifically, the logistics process of a manufacturing company. The study is based on a hybrid simulation of logistics in a manufacturing company that implemented the AnyLogic framework. The hybrid simulation is modelled using the BPMN notation using BIMP, the business process modelling software, to acquire data in the form of event logs. Next, five chosen automated process discovery techniques are applied to the event logs, and the results are evaluated. Based on the evaluation of benchmark results received using the chosen discovery algorithms, it is evident that the discovery algorithms have a better overall performance using more extensive event logs both in terms of fitness and precision. Nevertheless, the discovery techniques perform better in the case of smaller data sets, with less complex process models. Typically, automated discovery techniques have to address scalability issues due to the high amount of data present in the logs. However, as demonstrated, the process discovery techniques can also encounter issues of opposite nature. While discovery techniques typically have to address scalability issues due to large datasets, in the case of companies with long delivery cycles, long processing times and parallel production, which is common for the industrial sector, they have to address issues with incompleteness and lack of information in datasets. The management of business companies is becoming essential for companies to stay competitive through efficiency. The issues encountered within the simulation model will be amplified through both vertical and horizontal integration of the supply chain within the Industry 4.0. The impact of vertical integration in the BPMN model and the chosen case identifier is demonstrated. Without the assumption of smart manufacturing, it would be impossible to use a single case identifier throughout the entire simulation. The entire process would have to be divided into several subprocesses.
Šárka Čemerková, Jarmila Šebestová and Roman Šperka
cBackground and Purpose: Part-time employment could be seen as a modern form of employment or a type of innovative organizational change. The average share of part-time jobs in the Czech Republic in the observed period of 2004-2016 was 3.9 % according to the OECD, in comparison to the average OECD value of 16.6%. The main question to arise was, are there any regional differences? The presented conclusions are based on a regional study in the Moravian-Silesian Region (MSR) in the Czech Republic where the median value of part- time jobs is 10%. The main goal is to evaluate the regional level of part-time job offers and identify the main opportunities and obstacles which cause the low number of these job positions. Design/Methodology/Approach: The paper is based on a quantitative study using a questionnaire-based survey, comprising 215 respondents - owners of small and medium-sized enterprises (SMEs) in the Moravian-Silesian Region in the Czech Republic. The survey consists of 16 questions in three main areas: (i) Entrepreneurial motivation (1 item), (ii) External factors - Labour market problems (4 items), and (iii) Internal factors. Secondary information such as the results of earlier studies and regional government websites were used for data results comparison. All variables are compared in the context of the branch of business, number of employees, turnover, and age. Finally, a factor analysis was used to find the main way how to improve part-time job offers. Results: The variety of businesses and different regional locations opens up space for discussion regarding parttime job support. A factor analysis found five significant issues, which could affect local labour market and company behaviour. Conclusion: The added value of the paper can be seen in the factor identification, where internal willingness to support part-time employment and qualification growth as organizational change must be in first place.